InfoQ Homepage Articles
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Artificial Intelligence-Driven Phishing: How Phishing Technique Is Evolving and Implemented
In this article, the author examines how AI is transforming phishing from a manual, targeted activity into an automated and scalable attack model. The article breaks down each stage of the phishing lifecycle, showing how AI improves reconnaissance, profiling, content generation, delivery, and interaction, while outlining layered defenses that combine controls, processes, and user awareness.
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The Technology Adoption Curve, Twenty Years On
Today, June 8th, InfoQ celebrates 20 years. This is not a comprehensive history, but a deliberately selective look at the technologies and practices InfoQ identified early, where they sit on the adoption curve in 2026, and how that curve may evolve over the next five to ten years.
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Article Series: Securing the AI Stack: from Model to Production
This series provides your roadmap for the machine age, exploring how to move from vulnerable prototypes to resilient systems through layered defense, robust MLOps, and integrated governance.
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Architectural Change Cases: a Practical Tool for Evolutionary Architectures
Architectural change cases extend architecture decision record (ADR) thinking by evaluating how decisions may evolve over time. Change cases expose hidden assumptions and help teams estimate the reversibility and cost of change.
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Two Misconfigurations That Caused Spark OOM Failures on Kubernetes
After migrating Spark pipelines to Azure Kubernetes Service, two infrastructure settings interacted destructively: spark.kubernetes.local.dirs.tmpfs=true backed shuffle spill with RAM instead of disk, and a hard podAffinity rule forced all executors onto one node. Together, they caused repeated OOM kills invisible to standard diagnostics.
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/articles/vector-search-hybrid-retrieval-rag/en/smallimage/vector-search-hybrid-retrieval-rag-thumbnail-1779972811121.jpg)
Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG
In this article, author Aaditya Chauhan discusses the limitations of RAG pipelines based purely on vector search and how an internal omni-search application using Reciprocal Rank Fusion (RRF) that combines BM25 and vector results, can enhance the search solution.
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/articles/solving-ai-productivity-paradox-test-automation/en/smallimage/solving-ai-productivity-paradox-test-automation-thumbnail-1779953915743.jpg)
The AI Productivity Paradox in Test Automation: Moving beyond Structural Validation to Perception and Intent
The AI productivity paradox states that AI scales whatever abstraction it is built on. If that abstraction is structurally brittle, it scales structural brittleness. This article shows that to build a future of reliable, AI-driven test automation, we must stop scaling DOM-centric abstractions and build a new testing paradigm grounded in perception and intent.
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Stragglers, Not Failures: How Adaptive Hedged Requests Reduce p99 Latency by 74 Percent
In fan-out microservice architectures, slow-but-completing requests accumulate across services and drive p99 latency far higher than per-service metrics suggest. This article presents an adaptive hedging mechanism that uses DDSketch for real-time quantile estimation, windowed rotation to handle distribution drift, and a token-bucket budget to prevent load amplification.
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/articles/architecting-cloud-native-kafka/en/smallimage/architecting-cloud-native-kafka-thumbnail-1779433382367.jpg)
Architecting Cloud-Native Kafka: from Tiered Storage towards a Diskless Future
This article explores Kafka's transition toward a cloud-native architecture, examining how tiered storage, FinOps telemetry, elastic consumer scaling, virtual clusters, and Share Groups reshape the operational and economic model of event streaming platforms. It also analyzes emerging diskless-storage proposals and their architectural trade-offs.
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/articles/schema-proliferation-problem/en/smallimage/schema-proliferation-problem-thumbnail-1779270222602.jpg)
The Schema Proliferation Problem in Kafka and Flink Pipelines: How to Solve It
Schema proliferation builds slowly and gets expensive fast. One schema per event type feels right until there are ten tables, union queries spanning all of them, and a single field rename touching every schema. Discriminator-based schema consolidation collapses that to two tables, turning multi-table unions into a single query, while new variants are additive and don't break existing consumers.
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/articles/capacity-planning-queue-recovery/en/smallimage/The-Mathematics-of-Backlogs-Capacity-Planning-for-Queue-Recovery-thumb-1778227922596.jpg)
The Mathematics of Backlogs: Capacity Planning for Queue Recovery
Backlogs in distributed systems are arithmetic problems, not mysteries. This article provides practical formulas for calculating backlog drain time, sizing consumer headroom, and setting auto-scaling triggers. It covers key failure modes — retry amplification, metastable states, and cascading pipeline bottlenecks — plus when to shed load instead of draining.
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/articles/ebpf-for-security-observability/en/smallimage/ebpf-for-security-observability-thumbnail-1778674557176.jpg)
Kernel-Level Ground Truth: Why eBPF is Replacing User-Space Agents for Security Observability
eBPF is emerging as a preferred method for security observability over traditional user-space agents. By attaching probes directly to the Linux kernel's syscall interface, it provides consistent visibility even during container-level compromises. eBPF reduces security-related CPU consumption and limits data volume by performing filtering at the kernel level, enhancing operational efficiency.